A novel particle filter for multiple target tracking with track-before-detect measurement models is proposed. Particle filters efficiently perform target tracking under nonlinear or non-Gaussian models. However, their application to multiple target tracking suffers from the curse of dimensionality. We introduce an efficient particle filter for multiple target tracking which deals with the curse of dimensionality better than previously developed methods. The proposed algorithm is tested and compared to other multiple target tracking particle filters.
|Number of pages||14|
|Journal||IEEE Transactions on Aerospace and Electronic Systems|
|Publication status||Published - Oct 2017|
|MoE publication type||A1 Journal article-refereed|
- MULTITARGET TRACKING
- CONVERGENCE RESULT